水利水电技术2018，Vol.49Issue(1)：70-74,5.DOI:10.13928/j.cnki.wrahe.2018.01.010
基于NMEA-BP大坝变形监测模型研究
NMEA-BP based study on dam deformation monitoring model
摘要
Abstract
On the basis of the improvement of the mind evolutionary algorithm (MEA),the mind evolutionary algorithm and BP neural network-based study on dam deformation monitoring model is carried out herein.Through introducing the niche technology and mind evolutionary algorithm into the study,the defects of the BP neural network,such as being prone to fall into local optimal value,long training time,slow convergence rate,etc.,are overcome,and then its search efficiency and global search ability are greatly enhanced.Moreover,the weights and thresholds of the BP neural network are optimized by further application of the improved mind evolutionary algorithm,and then the NMEA-BP dam deformation monitoring model is not only established,but is also applied to the fitting and prediction of the actual engineering cases concerned.The result shows that the precision of dam deformation prediction is effectively enhanced by the NMEA-BP model,by which dam deformation monitoring can be efficiently and accurately carried out.The study result can provide references for the studies on both the theory and practice of dam deformation monitoring.关键词
小生境技术/思维进化算法/BP神经网络/大坝变形/监测模型Key words
Niche technology/mind evolutionary algorithm/BP neural network/dam deformation/monitoring model分类
水利科学引用本文复制引用
贾强强,苏怀智,郭芝韵,李丹,李鹏鹏..基于NMEA-BP大坝变形监测模型研究[J].水利水电技术,2018,49(1):70-74,5.基金项目
国家自然科学基金项目(51579083,51479054) （51579083,51479054）
国家重点研发计划项目(2016YFC0401601) （2016YFC0401601）
